Abstract: Embodiments implement a prediction-driven, rather than a trial-driven, approach to automatic data placement recommendations for partitioning data across multiple nodes in a database system. The system is configured to extract workload-specific features of a database workload running at a database system and dataset-specific features of a database running on the database system. The workload-specific features characterize utilization of the database workload. The dataset-specific features characterize how data is organized within the database. The system identifies a plurality of candidate keys for determining how to partition data stored in the database across nodes. Based at least in part on the workload-specific features, the dataset specific features, and the plurality of candidate keys, a set of candidate key combinations for partitioning data is generated.

Abstract: Techniques are described for executing machine learning models trained for specific operators with feature values that are based on the actual execution of a workload set. The machine learning models generate an estimate of benefit gain/cost for executing operations on data portions in the alternative encoding format. Such data potions may be sorted based on the estimated benefit, in an embodiment. Using cost estimation machine learning models for memory space, the data portions with the most benefits that comply with the existing memory space constraints are recommended and/or are automatically encoded into the alternative encoding format.

Abstract: Techniques are described for executing machine learning models trained for specific operators with feature values that are based on the actual execution of a workload set. The machine learning models generate an estimate of benefit gain/cost for executing operations on data portions in the alternative encoding format. Such data potions may be sorted based on the estimated benefit, in an embodiment. Using cost estimation machine learning models for memory space, the data portions with the most benefits that comply with the existing memory space constraints are recommended and/or are automatically encoded into the alternative encoding format.

Abstract: Embodiments implement a prediction-driven, rather than a trial-driven, approach to automatic data placement recommendations for partitioning data across multiple nodes in a database system. The system is configured to extract workload-specific features of a database workload running at a database system and dataset-specific features of a database running on the database system. The workload-specific features characterize utilization of the database workload. The dataset-specific features characterize how data is organized within the database. The system identifies a plurality of candidate keys for determining how to partition data stored in the database across nodes. Based at least in part on the workload-specific features, the dataset specific features, and the plurality of candidate keys, a set of candidate key combinations for partitioning data is generated.

Abstract: A method of presenting personalized additional information along with displayed content includes accessing a content viewing history and a user profile. Detecting an event by extracting metadata related to content provided for display, the content provided for display related to other content not contained within the content viewing history, and accessing additional information related to the detected event. Additional features include overlaying an object onto the content being displayed on the content display device, and displaying background image information the surrounds the content display device in the view of the AR user. Any or all of the features may be present simultaneously.

Abstract: A method for correlating Galvanic Skin Response (GSR) signals from multiple users watching the same content to identify scenes of interest in such content includes filtering GSR signals from each user by subtracting consecutive GSR signal samples from each other. The user reaction portion and baseline portion of the GSR signals for the users are collectively optimized to recover non-zero user responses for the users. The locations in the content having the non-zero responses for the users are then identified as the scenes of interest in such content for the users.

Abstract: The present disclosure provides a method (500) and apparatus (1000, 250) for using the biometric responses of a first group of users watching and/or listening to digital multimedia content to generate a summary of the digital multimedia content by randomly selecting segments from the digital multimedia content as a function of segment scores determined from the biometric responses. In another method (600) and apparatus (1000, 250) of the present disclosure, the biometric responses of a second group of users being shown the generated summary of the digital multimedia content can be used to extrapolate the biometric responses of the second group of users to the entire digital multimedia content. Furthermore, yet another method (650) and apparatus (1000, 250) of the present disclosure can use the biometric responses of at least one user in the second group of users to generate recommendations.

Abstract: The present principles generally relate to augmented reality (AR) apparatuses and methods, and in particular, to an exemplary augmented reality system (100) in which content characteristics are used to affect the individual viewing experience of the content. One exemplary embodiment involves a user specified modification of the content by using an augmented reality device to provide a preview (600) for a parent or a guardian of a viewer, or a third-party curator of contents. A modified content (705, 05) may be created by replacing or obscuring the objectionable content or scenes of the one or more of the original contents. The apparatus and method is employed in a system having one or more augmented reality devices (125-1-125-n) such as e.g., one or more pairs of AR glasses. The system may also include a non-AR display screen (191, 192) to display the content to one or more viewers. Accordingly, different forms of the same content may be presented on the different AR glasses and also on the shared screen.

Abstract: The present disclosure provides a method (500) and apparatus (1000, 250) for using the biometric responses of a first group of users watching and/or listening to digital multimedia content to generate a summary of the digital multimedia content by randomly selecting segments from the digital multimedia content as a function of segment scores determined from the biometric responses. In another method (600) and apparatus (1000, 250) of the present disclosure, the biometric responses of a second group of users being shown the generated summary of the digital multimedia content can be used to extrapolate the biometric responses of the second group of users to the entire digital multimedia content. Furthermore, yet another method (650) and apparatus (1000, 250) of the present disclosure can use the biometric responses of at least one user in the second group of users to generate recommendations.

Abstract: The present principles generally relate to augmented reality (AR) apparatuses and methods, and in particular, to an exemplary augmented reality system (100) in which content characteristics are used to affect the individual viewing experience of the content. One exemplary embodiment involves a user specified modification of the content by using an augmented reality device (125-1) to provide a preview for a parent or a guardian of a viewer, or a third-party curator of contents a time period before a potentially objectionable scene is to be shown to other viewers. A modified content (705, 1005) may be created by replacing or obscuring the objectionable content or scenes of the one or more of the original contents. The apparatus and method is employed in a system having one or more augmented reality devices (125-1-125-n) such as e.g., one or more pairs of AR glasses. The system may also include a non-AR display screen (191, 192) to display the content to one or more viewers.

Abstract: A method of presenting personalized additional information along with displayed content includes accessing a content viewing history and a user profile. Detecting an event by extracting metadata related to content provided for display, the content provided for display related to other content not contained within the content viewing history, and accessing additional information related to the detected event. Additional features include overlaying an object onto the content being displayed on the content display device, and displaying background image information the surrounds the content display device in the view of the AR user. Any or all of the features may be present simultaneously.